512 engineering-computation-"https:"-"https:"-"https:"-"https:"-"https:"-"LGEF" PhD positions in United Kingdom
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professional development workshops in areas such as research communication, computing and data science, and professional progression through our Early Career Researcher Institute .Additionally, you will be
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-skills) or equivalent language qualification. International applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on
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supported by PEACEPLUS, a programme managed by the Special EU Programmes Body (SEUPB) involving a range of partner organisations. NWCAM2 is an initiative seeking to help small and medium sized enterprises
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Research Assistant to investigate digital reading comprehension through large-scale data analysis. This role, funded by the John Fell Fund, sits at the fascinating intersection of computational
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(Centre for Doctoral Training in Modelling of Heterogeneous Systems) at the University of Warwick is an innovative, interdisciplinary fully funded PhD programme that brings together science, engineering
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This PhD forms part of an ongoing collaboration between IBM and the Department of Engineering at the University of Cambridge, centred on the mathematical and computational modelling of Earth and
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. In particular, C-dots can be engineered to sensitively detect intracellular pH fluctuations, which are critical in cellular health and disease, and extended to other analytes relevant for both
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may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply Please read and complete this document as
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. The successful candidate will work closely with the project sponsors to deliver the outputs and will have access to a bespoke training programme. This project will deliver a model that integrates water quality to
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap